Tropical Sea Surface Temperature (SST) Forecasts

El Niño is a global phenomenon involving complex interactions
within the ocean-atmosphere system. Although a single index cannot
describe the dynamics of El Niño, a single field, the sea surface
temperatures (SSTs), provides a remarkably efficient summary of the
timescales inherent in El Niño dynamics. PSD researchers use a
dynamically-based statistical technique, Linear Inverse Modeling
(LIM) to identify the evolutionary behavior of dynamical SST modes
in the tropical oceans. The results of this technique allow
experimental forecasts of tropical SSTs with skill competitive with
that of numerical climate forecast models.

LIM forecasts are part of a consolidated effort of the National
Oceanic and Atmospheric Administration (NOAA), NOAA's National
Weather Service, and their funded institutions. For more
information, see NOAA's Climate Diagnostic Bulletin.

Methods

SST anomalies are calculated relative to 1981-2010 climatology,
smoothed by a three months' running mean, and projected onto a
basis of 20 Empirical Orthogonal Functions (EOFs). This last step
consolidates most of the predictable information contained in a map
of tropical SSTs into a practical number of data structures. Using
this reduced space, the lagged and contemporaneous covariance
structure of SSTs is used to generate the best linear dynamical
model of the multivariate SST field. Forecasts using this model
are then made, and forecast error is analyzed to verify the
validity of the linear model. More information about the method is
available from Penland and Sardeshmukh (1995).